Using pandas, I want to export a DataFrame with mixed data types to a CSV file with complete numeric display instead of scientific formatting. How can this be done? See example:
import pandas as pd
import numpy as np
data_collection = {'label': ['alpha', 'beta', 'gamma'], 'metric': np.array([3.14159265e+12, 2.71828182e+13, 1.61803399e+14])}
df_custom = pd.DataFrame(data_collection)
df_custom.to_csv('result.csv', float_format='%.8f', index=False)
hey, try converting numbres to str with your desired decimals before export. that often bypasses the sciensific notation and keeps full precision in the csv. hope it helps, cheers!
An alternative method involves formatting the numeric columns directly before exporting. One approach is to use the DataFrame’s apply method on the numeric column to convert the numbers to strings with the desired formatting. This bypasses the default scientific notation since the numbers are no longer in float format. Additionally, setting the display options temporarily through pd.option_context could also be beneficial if you want to see the changes in the notebook. In my work, directly converting problematic columns has proven to be effective and straightforward.
In my experience, another effective approach when dealing with mixed-data columns in pandas is to define a custom formatter. Instead of globally converting the numbers to strings using apply, you can temporarily store the formatted numbers in a new column or create a formatting function that returns a formatted string, then export that. This method gives you granular control over each column’s format without permanently altering the data types within the DataFrame. I found this especially useful when needing to both preserve numeric precision and avoid scientific notation issues in the CSV file.
hey, u can globally disable sci fmt using pd.options.display.float_format = lambda x: ‘%.8f’ % x before export. works fine, just rmeber to reset it after if needed.
In cases where setting the float_format parameter alone doesn’t work, another viable approach is to explicitly modify the numeric column formatting before the export. I have encountered scenarios where I needed to preserve the exact numeric form while still keeping the column as a numeric type for further processing in other steps. One solution is to format the column values and assign them back once formatted with a precision specifier, then convert them back to numbers after export if necessary. This method gives me control over formatting on a per-column basis without altering the inherent data structure or requiring permanent type changes.